People Analytics & Reporting at Baylor Scott & White Health. View the Q-and-A below to see how Jonathon Frampton has incorporated predictive analytics into the workforce of Baylor Scott & White Health. Also, glimpse what’s in store for the new PAW Workforce conference.

Q: How is a specific line of business / business unit using your predictive decisions? How is your product deployed into operations?

A: We are in a state of constant iteration/development with our deliverables and since most of our current work shows up in presentation form much of the final use is masked to us. This is actually a point of current focus for our team, capturing our “#wins” as we call them when our data / inference are used for the greater good. Much of our current deployment focus around the enablement of our HR business partners and directors. This team has been very quick to run with our results and distribute them into the workforce as needed.

Q: If HR were 100% ready and the data were available, what would your boldest data science creations do?

A: I LOVE this question! We focus on creating a more efficient experience for our people leaders, as such an area ready for an end to end predictive / prescriptive solution would handle the entire process how our workforce is staffed and how mobile employees are deployed. A solution that would only create, approve and source positions as they become predictively necessary given parameters that include elements of productivity and employee satisfaction would free up our leaders time to focus on our patient care. Taking it a step further allows for thinner more qualified slate of candidate to be presented in a timely manner, given that our recruiting force would know well ahead of time what pipelines need to be tapped and ready!

Q: When do you think businesses will be ready for “black box” workforce predictive methods, such as Random Forests or Neural Networks?

A: I am not sure that the businesses like the business of people will ever be 100% ready, or even that they should be. It is one thing to set a model churning our trades at a nanoseconds pace, but can you imagine making a decision on someone’s future as quickly? That being said, if the focus of workforce predictive analytics was less on the true HR work and focused on people enablement actions the adoption rate would be much quicker.

Q: Do you have suggestions for data scientists trying to explain the complexity of their work, to those solving workforce challenges?

A: This is a great question and one I am sure many are grappling with. Like many we are pretty young in this game, so I can speak to how we are currently seeing success in this area. We have gone with an internal consultant model for our organization. Our group does sit within HR, but we have an individual (consultant) wholly focused on taking the work of our analysts and educating, training and enabling our HR professionals to gain full value of it. This has been a huge bonus for us as the street flows in both directions and has turned into a wonderful quantitative / qualitative feedback loop of their commentary flowing in our direction feeding increasingly relevant results to theirs.

Q: What is one specific way in which predictive analytics actively is driving decisions?

A: As we are a very young group we do not yet have any direct results from a predictive product driven decision as the majority of our deliverables have been inferential in nature allowing our business partners and operations teams to infer the predictive nature of the data. This is by design as the idea of jumping from a finally standardized set of HR KPIs directly into predicting results can (and should) be quite overwhelming for our customers, however we are rolling out bits and pieces as I type so look for great things soon.

Q: How does business culture, including HR, need to evolve to accept the full promise of predictive workforce?

A: I think the (re)evolution has already begun, but it is far from over. What we need is the consistent delivery of increasingly complex results from HR data. I think we (HR) will follow the same trajectory seen by marketing in recent years with adoption following an exponential curve after hitting a “tipping point” a number of years in. Additionally a strong focus on educating our operational customers on the uses and values of our people insights would speed adoption rates and create more of a pull effect.

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